Jason L. Granstedt

According to our database, Jason L. Granstedt authored at least 8 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Learned Hotelling observers for use with multi-modal data.

Jason L. Granstedt, Fu Li, Umberto Villa, Mark A. Anastasio

Proceedings of the Medical Imaging 2022: Image Perception, 2022

2021

Impact of deep learning-based image super-resolution on binary signal detection.

Xiaohui Zhang, Varun A. Kelkar, Jason L. Granstedt, Hua Li, Mark A. Anastasio

CoRR, 2021

Advancing the AmbientGAN for learning stochastic object models.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

Task-based evaluation of deep image super-resolution in medical imaging.

Varun A. Kelkar, Xiaohui Zhang, Jason L. Granstedt, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks.

Jason L. Granstedt, Varun A. Kelkar, Weimin Zhou, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021

2020

Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks.

Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio

CoRR, 2020

Learning efficient channels with a dual loss autoencoder.

Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio

Proceedings of the Medical Imaging 2020: Image Perception, 2020

2019

Autoencoder embedding of task-specific information.

Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio

Proceedings of the Medical Imaging 2019: Image Perception, 2019